R: Predictions from an Inbagg Object

predict.inbagg {ipred} | R Documentation

## Predictions from an Inbagg Object

### Description

Predicts the class membership of new observations through indirect bagging.

### Usage

    ## S3 method for class 'inbagg'
    predict(object, newdata, ...)

### Arguments

`object` | object of class `inbagg`, see `inbagg`.
`newdata` | data frame to be classified.
`...` | additional argumends corresponding to the predictive models.

### Details

Predictions of class memberships are calculated. i.e. values of the intermediate variables are predicted following `pFUN` and classified following `cFUN`, see `inbagg`.

### Value

The vector of predicted classes is returned.

### References

David J. Hand, Hua Gui Li, Niall M. Adams (2001), Supervised classification with structured class definitions. Computational Statistics & Data Analysis 36, 209–225.

Andrea Peters, Berthold Lausen, Georg Michelson and Olaf Gefeller (2003), Diagnosis of glaucoma by indirect classifiers. Methods of Information in Medicine 1, 99-103.

### See Also

`inbagg`

### Examples

    library("MASS")
    library("rpart")
    y <- as.factor(sample(1:2, 100, replace = TRUE))
    W <- mvrnorm(n = 200, mu = rep(0, 3), Sigma = diag(3))
    X <- mvrnorm(n = 200, mu = rep(2, 3), Sigma = diag(3))
    colnames(W) <- c("w1", "w2", "w3")
    colnames(X) <- c("x1", "x2", "x3")
    DATA <- data.frame(y, W, X)

    pFUN <- list(list(formula = w1~x1+x2, model = lm),
    list(model = rpart))

    RES <- inbagg(y~w1+w2+w3~x1+x2+x3, data = DATA, pFUN = pFUN)
    predict(RES, newdata = X)

[Package ipred version 0.9-6 Index]